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Understanding the Rising Phase of the PM(2.5) Concentration Evolution in Large China Cities

Long-term air quality observations are seldom analyzed from a dynamic view. This study analyzed fine particulate matter (PM(2.5)) pollution processes using long-term PM(2.5) observations in three Chinese cities. Pollution processes were defined as linearly growing PM(2.5) concentrations following th...

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Autores principales: Lv, Baolei, Cai, Jun, Xu, Bing, Bai, Yuqi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5404509/
https://www.ncbi.nlm.nih.gov/pubmed/28440282
http://dx.doi.org/10.1038/srep46456
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author Lv, Baolei
Cai, Jun
Xu, Bing
Bai, Yuqi
author_facet Lv, Baolei
Cai, Jun
Xu, Bing
Bai, Yuqi
author_sort Lv, Baolei
collection PubMed
description Long-term air quality observations are seldom analyzed from a dynamic view. This study analyzed fine particulate matter (PM(2.5)) pollution processes using long-term PM(2.5) observations in three Chinese cities. Pollution processes were defined as linearly growing PM(2.5) concentrations following the criteria of coefficient of determination R(2) > 0.8 and duration time T ≥ 18 hrs. The linear slopes quantitatively measured pollution levels by PM(2.5) concentrations rising rates (PMRR, μg/(m(3)·hr)). The 741, 210 and 193 pollution processes were filtered out, respectively, in Beijing (BJ), Shanghai (SH), and Guangzhou (GZ). Then the relationships between PMRR and wind speed, wind direction, 24-hr backward points, gaseous pollutants (CO, NO(2) and SO(2)) concentrations, and regional PM(2.5) levels were studied. Inverse relationships existed between PMRR and wind speed. The wind directions and 24-hr backward points converged in specific directions indicating long-range transport. Gaseous pollutants concentrations increased at variable rates in the three cities with growing PMRR values. PM(2.5) levels at the upwind regions of BJ and SH increased at high PMRRs. Regional transport dominated the PM(2.5) pollution processes of SH. In BJ, both local contributions and regional transport increased during high-PMRR pollution processes. In GZ, PM(2.5) pollution processes were mainly caused by local emissions.
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spelling pubmed-54045092017-04-27 Understanding the Rising Phase of the PM(2.5) Concentration Evolution in Large China Cities Lv, Baolei Cai, Jun Xu, Bing Bai, Yuqi Sci Rep Article Long-term air quality observations are seldom analyzed from a dynamic view. This study analyzed fine particulate matter (PM(2.5)) pollution processes using long-term PM(2.5) observations in three Chinese cities. Pollution processes were defined as linearly growing PM(2.5) concentrations following the criteria of coefficient of determination R(2) > 0.8 and duration time T ≥ 18 hrs. The linear slopes quantitatively measured pollution levels by PM(2.5) concentrations rising rates (PMRR, μg/(m(3)·hr)). The 741, 210 and 193 pollution processes were filtered out, respectively, in Beijing (BJ), Shanghai (SH), and Guangzhou (GZ). Then the relationships between PMRR and wind speed, wind direction, 24-hr backward points, gaseous pollutants (CO, NO(2) and SO(2)) concentrations, and regional PM(2.5) levels were studied. Inverse relationships existed between PMRR and wind speed. The wind directions and 24-hr backward points converged in specific directions indicating long-range transport. Gaseous pollutants concentrations increased at variable rates in the three cities with growing PMRR values. PM(2.5) levels at the upwind regions of BJ and SH increased at high PMRRs. Regional transport dominated the PM(2.5) pollution processes of SH. In BJ, both local contributions and regional transport increased during high-PMRR pollution processes. In GZ, PM(2.5) pollution processes were mainly caused by local emissions. Nature Publishing Group 2017-04-25 /pmc/articles/PMC5404509/ /pubmed/28440282 http://dx.doi.org/10.1038/srep46456 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Lv, Baolei
Cai, Jun
Xu, Bing
Bai, Yuqi
Understanding the Rising Phase of the PM(2.5) Concentration Evolution in Large China Cities
title Understanding the Rising Phase of the PM(2.5) Concentration Evolution in Large China Cities
title_full Understanding the Rising Phase of the PM(2.5) Concentration Evolution in Large China Cities
title_fullStr Understanding the Rising Phase of the PM(2.5) Concentration Evolution in Large China Cities
title_full_unstemmed Understanding the Rising Phase of the PM(2.5) Concentration Evolution in Large China Cities
title_short Understanding the Rising Phase of the PM(2.5) Concentration Evolution in Large China Cities
title_sort understanding the rising phase of the pm(2.5) concentration evolution in large china cities
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5404509/
https://www.ncbi.nlm.nih.gov/pubmed/28440282
http://dx.doi.org/10.1038/srep46456
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